Palm oil analysis in adulterated sesame oil using chromatography and FTIR spectroscopy

This study highlights the application of two analytical techniques, namely GC‐FID and FTIR spectroscopy, for analysis of refined‐bleached‐deodorized palm oil (RBD‐PO) in adulterated sesame oil (SeO). Using GC‐FID, the profiles of fatty acids were used for the evaluation of SeO adulteration. The increased concentrations of palmitic and oleic acids together with the decreased levels of stearic, linoleic, and linolenic acids with the increasing contents of RBD‐PO in SeO can be used for monitoring the presence of RBD‐PO in SeO. Meanwhile, FTIR spectroscopy combined with multivariate calibration of partial least square (PLS) has been successfully developed for the detection and quantification of RBD‐PO in SeO using the combined frequencies of 3040–2995, 1660–1654, and 1150–1050 cm^?1. The values of coefficient of determination (R²) for the relationship between actual versus FTIR‐calculated values of RBD‐PO in SeO and root mean square error of calibration (RMSEC) obtained are 0.997 and 1.32% v/v, respectively. In addition, using three factors, the root mean square error of prediction (RMSEP) value obtained using the developed PLS calibration model is relatively low, i.e., 1.83% v/v. Practical Application: The adulteration practice is commonly encountered in fats and oils industry. It involves the replacement of high value edible oils such as sesame oil with the lower ones like palm oil. Gas chromatography and FTIR spectroscopy can be used as reliable and accurate analytical techniques for detection and quantification of palm oil in sesame oil.     

Rapid Determination of Total Polar Compounds in Frying Oil Using ATR‐FTIR Combined with Extended Partial Least Squares Regression

A method of rapidly determining the total polar compounds (TPCs) in frying oils using attenuated total reflectance‐Fourier transform infrared spectroscopy combined with partial least squares (PLS) regression is developed. Oils of various types and geographic origins are used to ensure that the proposed model is robust. The first derivative spectrum is selected as the spectral processing method. The interval PLS, forward interval PLS, and backward interval PLS algorithms are compared in terms of their performance. A correlation coefficient (R²) of 0.9942, a root mean square error of calibration (RMSEC) of 1.1, a root mean square error of prediction (RMSEP) of 2.30, a residual predictive deviation (RPD) of 4.1, and a limit of detection (LOD) of 1.65% are obtained by the fiPLS33 model with fewer latent variables and a lower spectral interval number. In addition, sub‐models using a single type of oil showed higher performance (R² 0.9957–0.9998, RMSEC 0.12–0.92, RMSEP 0.79–1.58, RPD 4.79–9.64, LOD 0.66–1.26%) than the general model. The TPC models developed are accurate, stable, and adaptable, and they can be used to analyze general frying oil samples quickly, regardless of the oil type, and to analyze samples of specific oil types accurately. Practical applications: The content of TPCs is an important indicator of whether the oil has been overused and whether it will be harmful during the frying process. However, traditional chemical methods are time‐consuming, and they have not been used to determine large‐sized samples. In addition, due to a lack of regional optimization, most studies on determining TPCs with FTIR give unsatisfactory model performance. A general TPC model that incorporates several oil types and regional optimization is expected to improve prediction performance. Therefore, the proposed method represents a rapid and accurate tool for measuring TPCs in edible fats and oils.     

Determination of free fatty acids in crude palm oil and refined-bleached-deodorized palm olein using fourier transform infrared spectroscopy

A rapid direct Fourier transform infrared (FTIR) spectroscopic method using a 100 μ BaF₂ transmission cell was developed for the determination of free fatty acid (FFA) in crude palm oil (CPO) and refined-bleached-deodorized (RBD) palm olein, covering an analytical range of 3.0–6.5% and 0.07–0.6% FFA, respectively. The samples were prepared by hydrolyzing oil with enzyme in an incubator. The optimal calibration models were constructed based on partial least squares (PLS) analysis using the FTIR carboxyl region (C=O) from 1722 to 1690 cm⁻¹. The resulting PLS calibrations were linear over the range tested. The standard errors of calibration (SEC) obtained were 0.08% FFA for CPO with correlation coefficient (R ²) of 0.992 and 0.01% FFA for RBD palm olein with R ² of 0.994. The standard errors of performance (SEP) were 0.04% FFA for CPO with R ² of 0.998 and 0.006% FFA for RBD palm olein with R ² of 0.998, respectively. In terms of reproducibility (r) and accuracy (a), both FTIR and chemical methods showed comparable results. Because of its simpler and more rapid analysis, which is less than 2 min per sample, as well as the minimum use of solvents and labor, FTIR has an advantage over the wet chemical method.     

A new method for determining gossypol in cottonseed oil by FTIR spectroscopy

A new method was developed to determine the gossypol content in cottonseed oil using FTIR spectroscopy with a NaCl transmission cell. The wavelengths used were selected by spiking clean cottonseed oil to gossypol concentrations of 0–5% and noting the regions of maximal absorbance. Transmittance values from the wavelength regions 3600–2520 and 1900–800 cm⁻¹ and a partial least squares (PLS) method were used to derive FTIR spectroscopic calibration models for crude cottonseed, semirefined cottonseed, and gossypol-spiked cottonseed oils. The coefficients of determination (R ²) for the models were computed by comparing the results from the FTIR spectroscopy against those obtained by AOCS method Ba 8-78. The R ² were 0.9511, 0.9116, and 0.9363 for crude cottonseed, semirefined cottonseed, and gossypol-spiked cottonseed oils, respectively. The SE of calibration were 0.042, 0.009, and 0.060, respectively. The calibration models were cross-validated within the same set of oil samples. The SD of the difference for repeatability and accuracy of the FTIR method were better than those for the chemical method. With its speed (ca. 2 min) and ease of data manipulation, FTIR spectroscopy is a useful alternative to standard wet chemical methods for rapid and routine determination of gossypol in process and/or quality control for cottonseed oil.     

Rapid Determination of Free Fatty Acid in Extra Virgin Olive Oil by Raman Spectroscopy and Multivariate Analysis

We introduce a visible Raman spectroscopic method for determining the free fatty acid (FFA) content of extra virgin olive oil with the aid of multivariate analysis. Oleic acid was used to increase the FFA content in extra virgin olive oil up to 0.80% in order to extend the calibration span. For calibration purposes, titration was carried out to determine the concentration of FFA for the investigated oil samples. As calibration model for the FFA content (FFA%), a partial least squares (PLS) regression was applied. The accuracy of the Raman calibration model was estimated using the root mean square error (RMSE) of calibration and validation and the correlation coefficient (R ²) between actual and predicted values. The calibration curve of actual FFA% obtained by titration versus predicted values based on Raman spectra was established for different spectral regions. The spectral window (945–1600 cm⁻¹), which includes carotenoid bands, was found to be a useful fingerprint region being statistically significant for the prediction of the FFA%. High R ² and small RMSE values for calibration and validation could be obtained, respectively.     

Employment of Differential Scanning Calorimetry in Detecting Lard Adulteration in Virgin Coconut Oil

Lard (LD) has been commonly used as an adulterant in fats and oils. The similar physical characteristic of virgin coconut oil (VCO) to LD makes LD a desirable adulterant in VCO. Differential scanning calorimetry (DSC) provides unique thermal profiling for each oil and can be used to detect LD adulteration in VCO. In the heating thermogram of the mixture, there was one major endothermic peak (peak A) with a smaller shoulder peak embedded in the major peak that gradually smoothed out to the major peak as the LD% increased. In the cooling thermogram, there were one minor peak (peak B) and two major exothermic peaks, peak C which increased as LD% increased and peak D which decreased in size as the LD% increased. From Stepwise Multiple Linear regression (SMLR) analysis, two independent variables were found to be able to predict LD% adulteration in VCO with R ² (adjusted) of 95.82. The SMLR equation of LD% adulteration in VCO is 293.1 − 11.36 (T _e A) − 2.17 (T _r D); where T _e A is the endset of peak A and T _r D is the range of thermal transition for peak D. These parameters can serve as a good measurement index in detecting LD adulteration in VCO.     

Rapid Method for the Determination of Moisture Content in Biodiesel Using FTIR Spectroscopy

A new, rapid, and direct method was developed for the determination of moisture content in biodiesel produced from various types of oils using Fourier transform infrared (FTIR) spectroscopy with an attenuated total reflectance (ATR) element. Samples of biodiesels used in this study were produced using sludge palm oil (SPO). The calibration set was prepared by spiking double-distilled water into dried biodiesel samples in ratios (w/w) between 0 and 10% moisture. Absorbance values from the wavelength regions 3,700–3,075 and 1,700–1,500 cm⁻¹, and the partial least square (PLS) regression method were used to derive a FTIR spectroscopic calibration model for moisture content in biodiesel samples. The coefficient of determinations (R ²) for the models was computed by comparing the results obtained from FTIR spectroscopy against the values of the moisture concentrations (%) determined using the American Oil Chemists’ Society (AOCS) oven method Ca 2d-25. Same comparison was done using International Union of Pure and Applied Chemistry (IUPAC) distillation method 2.602. R ² was 0.9793 and 0.9700 using AOCS and IUPAC methods, respectively. The standard error (SE) of calibration was 1.84. The calibration model was cross validated within the same set of samples, and the standard deviation (SD) of the difference for repeatability (SDDr) and accuracy (SDDa) of the FTIR method was determined. With its speed and ease of data manipulation, FTIR spectroscopy is a useful alternative method to other methods for rapid and routine determination of moisture content in biodiesel for quality control.     

Analysis of Cod-Liver Oil Adulteration Using Fourier Transform Infrared (FTIR) Spectroscopy

Analysis of the adulteration of cod-liver oil with much cheaper oil-like animal fats has become attractive in recent years. This study highlights an application of Fourier transform infrared (FTIR) spectroscopy as a nondestructive and fast technique for the determination of adulterants in cod-liver oil. Attenuated total reflectance measurements were made on pure cod-liver oil and cod-liver oil adulterated with different concentrations of lard (0.5–50% v/v in cod-liver oil). A chemometrics partial least squares (PLS) calibration model was developed for quantitative measurement of the adulterant. Discriminant analysis method was used to classify cod-liver oil samples from common animal fats (beef, chicken, mutton, and lard) based on their infrared spectra. Discriminant analysis carried out using seven principal components was able to classify the samples as pure or adulterated cod-liver oil based on their FTIR spectra at the selected fingerprint regions (1,500–1,030 cm⁻¹).     

Multivariate calibration of fourier transform infrared spectra for determining thiobarbituric acid-reactive substance content in palm oil

Fourier transform infrared (FTIR) spectra of palm oil samples between 2900 and 2800 cm⁻¹ and 1800 and 1600 cm⁻¹ were used to compare different multivariate calibration techniques for quantitative determination of their thiobarbituric acid-reactive substance (TBARS) content. Fifty spectra (in duplicate) of palm oil with TBARS values between 0 and 0.25 were used to calibrate models based on partial least squares (PLS) and principal components regression (PCR) analyses with different baselines. The methods were compared for the number of factors, coefficients of determination (R ²), and accuracy of estimation. The standard errors of prediction (SEP) were calculated to compare their predictive ability. The calibrated models generated three to eight factors, R ² of 0.9414 to 0.9803, standard error of estimation (SEE) of 0.0063 to 0.0680, and SEP of 1.20 to 6.67.     

Determination of the Hydroxyl Value of Soybean Polyol by Attenuated Total Reflectance/Fourier Transform Infrared Spectroscopy

A rapid method for the quantitative determination of the hydroxyl value (OHV) of hydroxylated soybean oils by HATR/FTIR spectroscopy is described. Calibration standards were prepared by the formic acid/hydrogen peroxide method and OH values were determined by the official method of AOCS Tx 1a-66, covering an analytical range of 3.5–125 mg of KOH/g of sample. A partial least squares (PLS) calibration model for the prediction of the hydroxyl value (OHV) was developed based on eight different spectral subregions between 3,150 and 990 cm⁻¹ and combinations of them. On average, 36 samples were used for the modeling and 17 were used for external validation. The resulting calibration was linear over the analytical range and had a standard deviation of 2.334. Validation of the method was carried out by comparing the OHV of a series of hydroxylated soybean oils predicted by the PLS model to the values obtained by the AOCS standard method. A correlation coefficient of R ² = 0.9843 and RMSEC and RMSEP values of, respectively, 3.393 and 3.643 were obtained. After the calibration of the spectrometer, the OHV could be obtained in 2–3 min per sample, a major improvement over conventional wet chemical methods. The advantages of these methodologies are that they do not destroy the sample, have a lower cost, expedite the analysis and do not produce residues. Therefore, they may yield excellent results when used to quantify OHV of soybean polyols obtained by hydroxylation reaction.     

Rice bran FFA determination by diffuse reflectance IR spectroscopy

Rice bran with FFA levels above 0.1% cannot be used as a food ingredient due to oxidative off-flavor formation. However, extracting high FFA oil from bran by in situ methanolic esterification of rice bran oil to produce methyl ester biodiesel produces greater yields relative to low-FFA rice bran oil. Therefore, high-FFA bran could be exploited for biodiesel production. This study describes an FTIR spectroscopic method to measure rice bran FFA rapidly. Commercial rice bran was incubated at 37°C and 70% humidity for a 13-d incubation period. Diffuse reflectance IR Fourier transform spectra of the bran were obtained and the percentage of FFA was determined by extraction and acid/base titration throughout this period. Partial least squares (PLS) regression and a calibration/validation analysis were done using the IR spectral regions 4000-400 cm⁻¹ and 1731-1631 cm⁻¹. The diffuse reflectance IR Fourier transform spectra indicated an increasing FFA carbonyl response at the expense of the ester peak during incubation, and the regression coefficients obtained by PLS analysis also demonstrated that these functional groups and the carboxyl ion were important in predicting FFA levels. FFA rice bran changes also could be observed qualitatively by visual examination of the spectra. Calibration models obtained using the spectral regions 4000-400 cm⁻¹ and 1731-1631 cm⁻¹ produced correlation coefficients R and root mean square error (RMSE) of cross-validation of R=0.99, RMSE=1.78, and R=0.92, RMSE=4.67, respectively. Validation model statistics using the 4000-400 cm⁻¹ and 1731-1631 cm⁻¹ ranges were R=0.96, RMSE=3.64, and R=0.88, RMSE=5.80, respectively.     

The Use of FTIR Spectroscopy and Chemometrics for Rapid Authentication of Extra Virgin Olive Oil

The authenticity of high value edible fats and oils including extra virgin olive oil (EVOO) is an emerging issue, currently. The potential employment of Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of multivariate calibration and discriminant analysis has been exploited for rapid authentication of EVOO from canola oil (Ca‐O). The optimization of two calibration models of partial least square (PLS) and principle component regression was performed in order to quantify the level of Ca‐O in EVOO. The chemometrics of discriminant analysis (DA) was used for making the classification between pure EVOO and EVOO adulterated with Ca‐O. The individual oils and their blends were scanned on good contact with ZnSe crystals in horizontal attenuated total reflectance, as a sampling technique. The wavenumbers of 3,028–2,985 and 1,200–987 cm^?1 were used for quantification and classification of EVOO adulterated with Ca‐O. The results showed that PLS with normal FTIR spectra was well suited for quantitative analysis of Ca‐O with a value of the coefficient of determination (R²) > 0.99. The error, expressed as root mean square error of calibration obtained was relatively low, i.e. 0.108 % (v/v). DA can make the classification between pure EVOO and that adulterated with Ca‐O with one misclassified reported.     

RETRACTED ARTICLE: Investigation of Frying Oil Quality Using VIS/NIR Hyperspectral Analysis

Traditional chemical methods of analyzing frying oil quality are time-consuming and not amenable to on-line measurement. The main objective of this study was to evaluate quality changes of heated oils based on visible/near infrared spectral analysis using a hyperspectroradiometer. The reflectance spectra of the heated oils were analyzed within the range 400–1,750 nm. Acid value, total polar component, and viscosity of oil samples were used as indicators of different quality levels of oil. Partial least squares calibration models were developed for quantitative evaluations of these parameters. The R ² and root mean square error for each prediction were calculated to assess the prediction capability of calibration models. The study demonstrated that using the established calibration models, quality parameters could be predicted with R ² values over 0.92.     

Application of FTIR spectroscopy in determining sesamol in sesame seed oil

A new analytical method was developed for determining sesamol in sesame seed oil by FTIR spectroscopy. Sesamol was also spiked at 0 to 1000 mg/kg in freshly refined, bleached, and deodorized palm olein (RBDPOo) and groundnut (peanut) oil. FTIR spectra were recorded using a transmission (NaCl) cell accessory at room temperature, and the partial least squares regression statistical method was used to derive calibration models for each oil. The standard errors of calibration were 6.07, 5.88, and 4.24 mg/100 g for sesame, RBDPOo, and groundnut oils, with coefficients of determination (R ²) of 0.9947, 0.9940, and 0.9662, respectively. The calibration models were validated by the “leave-one-out” cross-validation method, and the R ² of validation, the standard errors of prediction, and SD of the differences for repeatability and accuracy were computed. Our results support the premise that FTIR spectroscopy is an efficient and accurate method for determining minor components such as sesamol in edible oils.     

Quantitative analysis of palm carotene using fourier transform infrared and near infrared spectroscopy

β-Carotene content is usually determined by using ultraviolet (UV)-visible spectrophotometry at 446 nm. In this study, two spectroscopic techniques, namely, Fourier transform infrared (FTIR) and near infrared (NIR) spectroscopy, have been investigated and compared to UV-visible spectrophotometry to measure the β-carotene content of crude palm oil (CPO). Calibration curves ranging from 200 to 800 ppm were prepared by extracting β-carotene from original CPO using open-column chromatography. Separate partial least squares calibration models were developed for predicting β-carotene based on the spectral region from 976 to 926 cm⁻¹ for FTIR spectroscopy and 546 to 819 nm for NIR spectroscopy. The correlation coefficient (R ²) and standard error of calibration obtained were 0.972 and 25.2 for FTIR and 0.952 and 23.6 for NIR techniques, respectively. The validation set gave R ² of 0.951 with standard error of performance (SEP) of 25.78 for FTIR technique and R ² of 0.979 with SEP of 19.96 for NIR technique. The overall reproducibility and accuracy did not give comparable results to that of spectrophotometric method; however, the standard deviation of prediction was still within ±5% β-carotene content over the range tested. Because of their rapidness and simplicity, both FTIR and NIR techniques provide alternative means of measuring β-carotene content in CPO. In addition, these two spectroscopic techniques are environmentally friendly since no solvent is involved.     

Multivariate determination of cloud point in palm oil using partial least squares and principal component regression based on FTIR spectroscopy

A rapid FTIR spectroscopic method was developed for quantitative determination of the cloud point (CP) in palm oil samples. Calibration samples were prepared by blending randomized amounts of palm olein and palm stearin to produce a wide range of CP values ranging between 8.3 and 47.9°C. Both partial least squares (PLS) and principal component regression (PCR) calibration models for predicting CP were developed by using the FTIR spectral regions from 3000 to 2800 and 1800 to 1600 cm⁻¹. The prediction capabilities of these calibration models were evaluated by comparing their standard errors of prediction (SEP) in an independent prediction set consisting of 14 palm oil samples. The optimal model based on PLS in the spectral range 1800-1600 cm⁻¹ produced lower SEP values (2.03°C) than those found with the PCR (2.31°C) method. FTIR in conjunction with PLS and PCR models was found to be a useful analytical tool for simple and rapid quantitative determination of CP in palm oil.     

Influence of pretreatment methods of the spectra on the calibration model of the precuring degree

In near infrared (NIR) spectra, there could be observed the baseline drift, background noise, scattering effects, and overlapped peaks. These errors can disturb the robustness and reliability of multivariate calibration models. Influences of spectral pretreatment methods on calibration model were studied. The partial least squares (PLS) were applied for developing model of the precuring degree. The multiplicative scatter correction gave the best values for R² and RMSEC. R² was 0.96, RMSEC was 0.112, respectively. The method NIR and reference method were compared using Student's t test (α = 0.05) for paired values, the result showed that there was no significant difference between the NIR method and the reference method. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Quantitative Analysis of Lard in Cosmetic Lotion Formulation Using FTIR Spectroscopy and Partial Least Square Calibration

Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of partial least squares (PLS) has been optimized for rapid determination of lard in a binary mixture with palm oil in a cosmetic lotion formulation. Lard, palm oil, and a binary mixture were extracted from matrix samples using liquid–liquid extraction, evaporated with a vacuum rotary evaporator, and the fat/oil yielded was further subjected to FTIR spectrometric measurement using attenuated total reflectance (ATR) as a sampling handling technique. The level of lard in the mixture with palm oil in the lotion formulation was quantified at frequency region of 1,200–1,000 cm^?1. The PLS calibration model reveals good correlation between the actual value of lard (x-axis) and the FTIR predicted value (y-axis) with a coefficient of determination (R²) of >0.99. Furthermore, the classification between lotions with and without lard in their formulation was performed using principal component analysis using the same frequency region used for quantification. The developed method was subsequently used for analysis of cosmetic lotions commercially available in the market. All samples analyzed did not contain lard in their formulations.     

Determination of phospholipids in vegetable oil by fourier transform infrared spectroscopy

A method was developed to determine the total phospholipid content in vegetable oil by Fourier transform infrared spectroscopy (FTIR). Calibration curves of I-α-phosphatidylcholine (PC), I-α-phosphatidylethanolamine (PE), and I-α-phosphatidylinositol (PI) in hexane were generated at different concentrations. The optimal phospholipid absorption bands between 1200–970 cm⁻¹ were identified and used for quantitative determination. High R ²≥0.968 were observed between band areas and phospholipid standard concentrations. Phospholipids from crude soybean oil were obtained by water degumming, and purification was performed on a silicic acid column. The phospholipid contents of purified phospholipid extract, degummed and crude soybean oil determined from calibration equations were >90, 0.0113, and 1.77%, respectively. High correlations of determination (R ²≥0.933) were observed between the FTIR method and thin-layer chromatography-imaging densitometry method for the determination of phospholipid content. FTIR was found to be a useful analytical tool for simple and rapid quantitative determination of phospholipids in vegetable oil.     

Determination of the SiH content of hydrogen silicone oil by a combination of the fourier transform near infrared,attenuated total reflectance–fourier transform infrared,and partial least squares regression models

To verify the feasibility of the determination of the Si?H content (HC) of hydrogen silicone oil (HS‐oil) with Fourier transform near infrared (FT‐NIR) spectroscopy and attenuated total reflectance (ATR)–Fourier transform infrared (FTIR) spectroscopy combined with the partial least squares regression (PLS‐R) model, HS‐oil samples were synthesized from concentrated hydrosilicone oil (HC = 1.4 wt %), octamethylcyclotetrasiloxane, and hexamethyldisiloxane or prepared by the dilution of concentrated hydrosilicone oil with octamethylcyclotetrasiloxane. The FT‐NIR PLS‐R model (8695–4000 cm^?1, two principal components) was developed from the FT‐NIR spectral data, and the coefficient of determination for cross‐validation (R²) and the coefficient of determination for external validation (r²) were 0.992 and 0.995, respectively. The ATR–FTIR PLS‐R model (2302–2040 cm^?1, one principal component) was developed from the ATR–FTIR spectral data; it produced an R² of 0.995 and an r² of 0.996. This study demonstrated that the combination of FT‐NIR and ATR–FTIR spectroscopy with the PLS‐R model were successfully used to determine the HC of the HS‐oil. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40694.